Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education
Open accessAbstract
The sudden popularity and availability of generative AI tools, such as ChatGPT that can write compelling essays on any topic, code in various programming languages, and ace standardized tests across domains, raises questions about the sustainability of traditional assessment practices. To seize this opportunity for innovation in assessment practice, we conducted a survey to understand both the educators' and students' perspectives on the issue. We measure and compare attitudes of both stakeholders across various assessment scenarios, building on an established framework for examining the quality of online assessments along six dimensions. Responses from 389 students and 36 educators across two universities indicate moderate usage of generative AI, consensus for which types of assessments are most impacted, and concerns about academic integrity. Educators prefer adapted assessments that assume AI will be used and encourage critical thinking, but students' reaction is mixed, in part due to concerns about a loss of creativity. The findings show the importance of engaging educators and students in assessment reform efforts to focus on the process of learning over its outputs, higher-order thinking, and authentic applications.
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0 of 8 cited sources checked · 0 supported · 0 flagged
- Findingown data
Educators have a strong preference for the adapted prompt.
“It shows that educators have a strong preference for the adapted prompt while students are less convinced by the adaptation, especially for the essay prompt.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
The assignment types rated to be least impacted by generative AI are presentations and discussions that are either pre-recorded or live.
“The assignment types rated to be least impacted are presentations and discussions that are either pre-recorded or live.”
Quote in the paperNot a substantial claim- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingreasoning
A similar pattern of drop and restoration was observed for students' ratings of the assessment's authenticity.
“A similar pattern was observed for students' ratings of the assessment's authenticity.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
About one in four students used ChatGPT weekly or daily for coursework (29% Australia; 24% US).
“However, only one in four students used it weekly or daily for coursework (29% Australia; 24% US) and for fun (25% Australia; 14% US).”
Quote in the paperNot a substantial claim - Findingown data
Students are less convinced by the adaptation, especially for the essay prompt.
“It shows that educators have a strong preference for the adapted prompt while students are less convinced by the adaptation, especially for the essay prompt.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
About one in four students used ChatGPT weekly or daily for fun (25% Australia; 14% US).
“However, only one in four students used it weekly or daily for coursework (29% Australia; 24% US) and for fun (25% Australia; 14% US).”
Quote in the paperNot a substantial claim - Findingown data
Educators used ChatGPT weekly or daily for fun (31% Australia; 40% US).
“Educators were using it weekly or daily for professional purposes (35% Australia; 10% US), for research (15% Australia; 30% US), and for fun (31% Australia; 40% US).”
Quote in the paperNot a substantial claim - Findingown data
Assessments that require product design or creative/artistic work are rated as moderately affected by generative AI.
“Assessments that require product design or creative/artistic work are also rated as moderately affected.”
Quote in the paperNot a substantial claim- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
The proposed adaptation to the original prompt was generally thought to restore the level of academic integrity.
“The proposed adaptation to the original prompt was generally thought to restore the level of academic integrity.”
Quote in the paperSubstantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
Educators used ChatGPT weekly or daily for professional purposes (35% Australia; 10% US).
“Educators were using it weekly or daily for professional purposes (35% Australia; 10% US), for research (15% Australia; 30% US), and for fun (31% Australia; 40% US).”
Quote in the paperNot a substantial claim - Findingown data
For both the essay and coding prompts, students and educators reported a substantial drop in the original prompt's capacity to ensure academic integrity due to the availability of ChatGPT.
“For both specific assessment scenarios (the essay and coding prompts), students and educators reported a substantial drop in the original prompt's capacity to ensure academic integrity due to the availability of ChatGPT.”
Quote in the paperSubstantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
Educators, especially in Australia, rated the impact of generative AI higher than students for all types of assignments.
“Educators, especially in Australia (Fig. 1), rated the impact of generative AI higher than students for all types of assignments.”
Quote in the paperNot a substantial claim- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
Students' open-ended responses indicated concern about a loss in creativity in the adapted essay prompt because it gave them an essay to critique instead of asking them to write one on their own.
“Open-ended responses from students indicated concern about a loss in creativity in the adapted essay prompt because it gave them an essay to critique instead of asking them to write one on their own:”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
Educators used ChatGPT weekly or daily for research (15% Australia; 30% US).
“Educators were using it weekly or daily for professional purposes (35% Australia; 10% US), for research (15% Australia; 30% US), and for fun (31% Australia; 40% US).”
Quote in the paperNot a substantial claim - Findingown data
Ratings of the other dimensions of assessment quality shown in Table 1 remained largely stable for students and educators.
“Yet ratings of the other dimensions of assessment quality shown in Table 1 remained largely stable for students and educators.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Findingown data
The study observed a surprising level of agreement across stakeholders and locales.
“Thus far, we have observed a surprising level of agreement across stakeholders and locals.”
Quote in the paperSubstantial claim- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
- Premisecitation
AI raises serious concerns about the validity of assessment practices, including issues of academic integrity, especially honesty and plagiarism.
“However, AI also raises serious concerns about the validity of assessment practices, including issues of academic integrity, especially honesty and plagiarism [3].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [3]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- May combine two claims. 11
- Classified as probably not a substantial claim. 12
- The quote only partly states this claim. 3
May combine two claims.
Findingown dataThe sample consists of 389 students and 36 educators from two selective institutions of higher education, one in Australia (338 students; 26 educators) and one in the United States (51 students; 10 educators).
“The sample we have collected thus far consists of 389 students and 36 educators from two selective institutions of higher education, one in Australia (338 students; 26 educators) and one in the United States (51 students; 10 educators).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAlmost every student and all educators in the sample have heard of ChatGPT.
“We find that almost every student and all educators in our sample have heard of ChatGPT.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenBesides ChatGPT, students and educators use tools like Anthropic, Bard, BingChat, ClaudeAI, DALL-E, Midjourney, and Stable Diffusion.
“Besides ChatGPT, students and educators use tools like Anthropic, Bard, BingChat, ClaudeAI, DALL-E, Midjourney, and Stable Diffusion.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAn important exception to the agreement is that students are more hesitant to endorse the adapted prompt than educators, for reasons including a perceived loss in creativity.
“An important exception is that students are more hesitant to endorse the adapted prompt than educators for reasons including a perceived loss in creativity.”
Quote in the paperSubstantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims. The quote only partly states this claim.
Findingown dataFor the coding assessment, students noted that they are already using various tools, such as Google or GitHub to search for similar codes, which is also widely accepted in the workplace.
“For the coding assessment, students noted that they are already using various tools:”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataStudents had forward-looking ethical concerns, including that students should be allowed to use generative AI tools to boost productivity as long as they can be accepted in their future workplace.
“Students also had forward-looking ethical concerns:”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
Probably not a substantial claim: may not pass S3 (load-bearing). The quote only partly states this claim.
Findingown dataSome students felt the adapted coding assessment replaces the teacher with ChatGPT, removing space for quality feedback.
“Students also raised concerns about the adapted coding assessment:”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataSome students preferred to learn how to write code than learn to analyse in the adapted coding assessment.
“Students also raised concerns about the adapted coding assessment:”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
May combine two claims.
Findingown dataThere was consensus among students and educators that essays (including reports, literature reviews, case studies, research papers), computer code (including pseudo-code, mathematical proofs), short-answer and multiple-choice questions are very or at least moderately impacted by generative AI.
“that essays (incl.reports, literature review, case studies, research papers), computer code (incl.pseudo-code, mathematical proofs), short-answer and multiple-choice questions are very or at least moderately impacted.”
Quote in the paperSubstantial claim- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
May combine two claims. The quote only partly states this claim.
Findingown dataStudents indicated that ChatGPT is useful to get them started as a prompt or inspiration but they would not use it directly as a source.
“Yet students also indicated that ChatGPT is useful to get them started”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
Classified as probably not a substantial claim.
Study design and conductreasoningThe study design yields a clear within-participant comparison of how the adaptation affects participants' judgement of assessment quality.
“This yields a clear within-participant comparison of how the adaptation affects their judgement of assessment quality.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationResearchers have identified several challenges educators face in designing and implementing new online assessments, including additional teacher time and effort, logistics and timing, technology access, consistency, functionality, alignment with student preferences, preparing students for new formats, and institutional policies.
“Researchers have identified several challenges educators face in designing and implementing new online assessments [4].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [4]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.
PremisecitationUnless educators and academic institutions adapt to generative AI, it can undermine academic integrity in online assessment and the purpose of higher education, and ultimately reduce the value of a university degree.
“Unless educators and academic institutions adapt to this new reality, generative AI can undermine academic integrity in online assessment and the purpose of higher education to educate students, and ultimately reduce the value of a university degree [1].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [1]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationOnline assessment presents practical challenges for student authentication and academic integrity: identity verification is especially difficult in online essays, and remote invigilation is challenging for online examinations.
“Online assessment presents practical challenges for student authentication and academic integrity: identity verification is especially difficult in online essays, and remote invigilation is challenging for online examinations [2,4].”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [2]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [4]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe framework for quality online assessment includes six design criteria and four contextual factors.
“Building on an extensive literature review, they identified six design criteria and four contextual factors at play (Figure 1).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [5]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Classified as probably not a substantial claim.
Study design and conductreasoningThe survey format and questions were almost identical for educators and students to enable comparison of their perspectives.
“The survey format and questions were almost identical for educators and students since our goal is to compare their perspectives.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationGenerative AI tools can write human-like text in a conversational style, and ChatGPT has been applied in language translation, chat bots, writing articles, stories, computer code, and other types of writing.
“Generative AI tools can write human-like text in a conversational style, and ChatGPT has been applied in language translation, chat bots for conversations with humans, writing articles, stories, computer code, and other types of writing [1].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [1]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Classified as probably not a substantial claim. May combine two claims.
Study design and conductcitationThe survey instrument was developed to evaluate the impact across various dimensions of online assessments and to evaluate similarities and differences between student and educator perspectives.
“The survey instrument we developed allows us to evaluate the impact across various dimensions of online assessments [5] and evaluate similarities and differences between the student and educator perspectives.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [5]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
The authors state this as an assumption.
The framework for online assessment quality is likely to generalize across countries.
“We believe that the framework is likely to generalize across countries and we are interested in examining if it can accurately reflect students' perspectives on assessment as well.”
The authors state this as an assumption.
In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
“Now consider the same assessment prompt again but in today's context when generative AI tools, such as ChatGPT, are widely available (i.e., students have equal access to the tool).”
The paper relies on this without support.
ChatGPT can write compelling essays on any topic, code in various programming languages, and ace standardized tests across domains.
“The sudden popularity and availability of generative AI tools, such as ChatGPT that can write compelling essays on any topic, code in various programming languages, and ace standardized tests across domains, raises questions about the sustainability of traditional assessment practices.”
The paper relies on this without support.
Pooling responses across the two institutions is valid for observing major trends.
“To analyze the data we have collected so far, we compute percentages and means of participants' ratings to observe major trends pooling across the two institutions.”
The paper relies on this without support.
Students can potentially use generative AI tools like ChatGPT to cheat on online assessments by submitting essays that are not their own work.
“Students can potentially use generative AI tools like ChatGPT to cheat on online assessments by submitting essays that are not their own work.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In a May 2023 survey of 3,017 high school and college students, nearly one-third admitted to using ChatGPT to complete their homework.
“In a survey by Intelligent.comconducted in May 2023 among 3,017 high school and college students, it was found that nearly one-third of the students admitted to using ChatGPT to complete their homework [6].”
From Survey on Plagiarism Detection in Large Language Models: The Impact of ChatGPT and Gemini on Academic Integrity (2024) · cites this paper as [6]
The Methods section reports a survey of 389 students and 36 educators at two higher-education institutions, not 3,017 high school and college students. Preliminary Findings report weekly or daily ChatGPT use for coursework (29% in Australia; 24% in the US), not that nearly one-third admitted using it to complete homework. Our copy does not mention an Intelligent.com survey. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredGenAI may erode students' critical thinking and reflection if used uncritically, leading to 'metacognitive laziness'.
“On the other, it may erode students' critical thinking and reflection if used uncritically, leading to what scholars have termed 'metacognitive laziness' (Fan et al., 2025;Smolansky et al., 2023).”
From Enhancing service-learning through Generative AI: a mixed-methods study on educational Game design in a finance course (2025) · cites this paper as Smolansky et al., 2023
The Preliminary Findings report students’ concerns about lost creativity and opportunities to learn in AI-adapted assessments, while the Discussion calls for assessments that center higher-order thinking. These passages support a general concern about learning, but do not say that uncritical GenAI use erodes critical thinking or reflection, or describe ‘metacognitive laziness.’ No page numbers are available in our copy. (LLM, conf=0.77)
Experimental — accuracy not yet measuredOur understanding of the sociotechnical implications of GenAI on an increasingly diverse student population is still in its infancy.
“While much of the discourse around students' use of GenAI tools has tended to focus on academic integrity concerns, our understanding of the sociotechnical implications on an increasingly diverse student population is still in its infancy [33, 41, 101, 116].”
From "I'd Never Actually Realized How Big An Impact It Had Until Now": Perspectives of University Students with Disabilities on Generative Artificial Intelligence (2025) · cites this paper as [101]
The Discussion (section 5; page unavailable) describes the study as ongoing, plans to examine differences across student backgrounds, and calls for attention to the interplay of technology, cognition, social interaction, and values. This supports the idea that understanding is still developing, but the paper does not establish that the student population is increasingly diverse or assess sociotechnical implications across that population broadly. (LLM, conf=0.82)
Experimental — accuracy not yet measuredEducators favor adapted assessments integrating GenAI to maintain academic integrity and encourage critical thinking.
“While educators favor adapted assessments integrating GenAI to maintain academic integrity and encourage critical thinking, students express mixed reactions, particularly concerning the loss of creativity [40].”
From Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda (2025) · cites this paper as [40]
Students express mixed reactions, particularly concerning the loss of creativity.
“While educators favor adapted assessments integrating GenAI to maintain academic integrity and encourage critical thinking, students express mixed reactions, particularly concerning the loss of creativity [40].”
From Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda (2025) · cites this paper as [40]
Initial research suggests that there may be gaps between students' and educators' opinions on how to achieve the best assessment approach.
“Although initial research (Smolansky et al., 2023) suggests that there may be gaps between students' and educators' opinions on how to achieve the best assessment approach, further research is required in this area.”
From The Artificial Intelligence Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment (2024) · cites this paper as Smolansky et al., 2023
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Impact ratings are attributed to the wrong figure
MinorThe text cites Figure 1 for Australian educators' and students' impact ratings, but the paper identifies Figure 2 as showing those ratings. Figure 1 is the assessment framework.
“Educators, especially in Australia (Fig. 1), rated the impact of generative AI higher than students for all types of assignments.”
“Figure: 2 Figure 2 : Figure 2: Australian educators' and students' ratings of how impacted different types of assessment are by generative AI.Mean ratings with standard error bars are shown.”
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Reimagining Higher Education: Navigating the Challenges of Generative AI Adoption
Hughes, L., Malik, T., Dettmer, S., Al-Busaidi, A. S., & Dwivedi, Y. K. (2025) · Information Systems Frontiers · doi:10.1007/s10796-025-10582-6 · Cited by 83 · see citing works
Interplay of rationality and morality in using ChatGPT for academic misconduct
Zhang, L., Amos, C., & Pentina, I. (2025) · Behaviour & Information Technology · doi:10.1080/0144929x.2024.2325023 · Cited by 48 · see citing works
“Therefore, among all assessment types, the focus of this study is written essays as the assignment most impacted by ChatGPT (Smolansky et al. 2023).”
Revell, T., Yeadon, W., Cahilly-Bretzin, G., Clarke, I., Manning, G., Jones, J., Mulley, C., Pascual, R. J., Bradley, N., Thomas, D., et al. (2024) · International Journal for Educational Integrity · doi:10.1007/s40979-024-00161-8 · Cited by 51 · see citing works
“The urgency for comprehensive insights into AI’s ramifications for both teaching and assessment has only intensified in an era where powerful generative AI tools are publicly-accessible (Zawacki-Richter et al. 2019).”
BackgroundCodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning Programming
Hou, X., Wu, Z., Wang, X., & Ericson, B. J. (2024) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3657604.3662032 · Cited by 51 · see citing works
Dotan, R., Parker, L. S., & Radzilowicz, J. (2024) · The 2024 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3630106.3659023 · Cited by 71 · see citing works
Early Perceptions of Teaching and Learning Using Generative AI in Higher Education
Damiano, A. D., Lauría, E. J. M., Sarmiento, C., & Zhao, N. (2024) · Journal of Educational Technology Systems · doi:10.1177/00472395241233290 · Cited by 42 · see citing works
“This supports previous literature, which addresses the concerns students have about Generative AI (Smolansky et al., 2023).”
ResultA survey on students’ use of AI at a technical university
Balabdaoui, F., Dittmann-Domenichini, N., Grosse, H., Schlienger, C., & Kortemeyer, G. (2024) · Discover Education · doi:10.1007/s44217-024-00136-4 · Cited by 41 · see citing works
“…of learning outcomes need to be adjusted, it is imperative to better understand how students are already incorporating these tools into their learning journeys [13, 40, 44], and thus several studies have already been conducted within the short amount of time that these tools were available [43].”
Generative AI Meets Open-Ended Survey Responses: Research Participant Use of AI and Homogenization
Zhang, S., Xu, J., & Alvero, A. (2025) · Sociological Methods & Research · doi:10.1177/00491241251327130 · Cited by 48 · see citing works
Bikanga Ada, M. (2024) · Education Sciences · doi:10.3390/educsci14101106 · Cited by 40 · see citing works
“This aligns with research emphasising the importance of designing assessments that test cognitive processes beyond the capabilities of genAI tools [15,67–70].”
InfluentialKeith, M. J., Keiller, E., Windows-Yule, C., Kings, I., & Robbins, P. T. (2025) · Education for Chemical Engineers · doi:10.1016/j.ece.2025.01.002 · Cited by 44 · see citing works
Van Wyk, M. M. (2024) · Journal of Applied Learning and Teaching · doi:10.37074/jalt.2024.7.1.15 · Cited by 35 · see citing works
Enlarged Education – Exploring the Use of Generative AI to Support Lecturing in Higher Education
Hennekeuser, D., Vaziri, D. D., Golchinfar, D., Schreiber, D., & Stevens, G. (2024) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-024-00424-y · Cited by 35 · see citing works
“Recently, Smolansky et al. ( 2023) published a concise report detailing the results of a survey where both students and lecturers expressed their concerns regarding the integration of LLMs into educational settings.”
Factors Influencing Educators’ Technostress While Using Generative AI: A Qualitative Study
Khlaif, Z. N., Hamamra, B. T., Bensalem, E., Mitwally, M. A. A., & Sanmugam, M. (2025) · Technology Knowledge and Learning · doi:10.1007/s10758-025-09885-z · Cited by 37 · see citing works
“Despite these challenging conditions, the findings of this study are consistent with previous research (Alasadi & Baiz, 2023; Çelebi et al., 2023 ; Smolansky et al., 2023; Wong et al., 2023 ), which identified several elements contributing to technostress among educators using GenAI in higher…”
Lee, Y. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13129-5 · Cited by 40 · see citing works
“Smolansky et al. (2023) investigated the perspectives of educators and students on the impact of GenAI on assessments in higher education.”
Pre-service Teacher Perceptions of ChatGPT for Lesson Plan Generation
Kalenda, P. J., Rath, L., Heidt, M. A., & Wright, A. (2024) · Journal of Educational Technology Systems · doi:10.1177/00472395241301388 · Cited by 32 · see citing works
“A study by Smolansky et al. (2023) revealed that some higher education students have reservations with using generative AI as it can be seen as sti fl ing creativity.”
Almazrou, S. H., Alanezi, F., Almutairi, S. A., AboAlsamh, H. M., Alsedrah, I. T., Arif, W. M., Alsadhan, A. A., Alsanad, D. S., Alqahtani, N. S., AlShammary, M. H., et al. (2024) · Nutrition and Health · doi:10.1177/02601060241273627 · Cited by 33 · see citing works
“Generative AI technologies like language models that produce human-like text responses are promising tools for teaching students critical thinking (Dai et al., 2023; Michel-Villarreal et al., 2023; Smolansky et al., 2023).”
Students’ Experience of a ChatGPT Enabled Final Exam in a Non-Majors Chemistry Course
Clark, M. J., Reynders, M., & Holme, T. A. (2024) · Journal of Chemical Education · doi:10.1021/acs.jchemed.4c00161 · Cited by 28 · see citing works
AI chatbots in programming education: guiding success or encouraging plagiarism
Akçapınar, G., & Sidan, E. (2024) · Discover Artificial Intelligence · doi:10.1007/s44163-024-00203-7 · Cited by 27 · see citing works
“In the literature, there are self-report-based studies that have reached the findings that GenAI affects students’ critical thinking by loss of creativity [28].”
Literature Review on the Integration of Generative AI in Programming Education
Nathaniel, J., Oyelere, S. S., Suhonen, J. T., & Tedre, M. (2025) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-025-00524-3 · Cited by 40 · see citing works
“The development of higher-order thinking skills is important in programming edu - cation, as it advances critical thinking (Smolansky et al., 2023), problem-solving (Kazemitabaar et al., 2023a, 2023b), and creativity (Kothari, 2023).”
Hwang, A. H., Siy, J. O., Shelby, R. M., & Lentz, A. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3661555 · Cited by 26 · see citing works
“Besides building a mutual understanding of speech content, Smolansky et al. stressed the importance of forming a consensus on whether, when, and how genAI should be used in learning; they found this common ground played a crucial role in trust building between teachers and students [94].”
BackgroundWang, K. D., Wu, Z., Tufts, L., Wieman, C., Salehi, S., & Haber, N. (2025) · 2025 IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon62633.2025.11016406 · Cited by 28 · see citing works
“For example, a survey for university instructors and students in the US and Australia revealed moderate usage of genAI tools for coursework and professional purposes [29].”
Atcheson, A., Khan, O., Siemann, B., Jain, A., & Karahalios, K. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714121 · Cited by 22 · see citing works
The Education Leadership Challenges for Universities in a Postdigital Age
Ellis, R. A. (2024) · Postdigital Science and Education · doi:10.1007/s42438-024-00461-9 · Cited by 29 · see citing works
“These concerns will require existing degree programme and course designs to be rethought in increasingly inter-disciplinary ways, along with new programmes from disciplinary areas which are yet to exist but are emergent (Smolansky et al. 2023).”
UNESCO's AI Competency Framework
Mutawa, A. M., & Sruthi, S. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-0884-4.ch004 · Cited by 24 · see citing works
Asking generative artificial intelligence the right questions improves writing performance
Cheng, Y., Fan, Y., Li, X., Chen, G., Gašević, D., & Swiecki, Z. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2025.100374 · Cited by 21 · see citing works
Whether and When Could Generative AI Improve College Student Learning Engagement?
Guo, F., Zhang, L., Shi, T., & Coates, H. B. (2025) · Behavioral Sciences · doi:10.3390/bs15081011 · Cited by 21 · see citing works
“These tools deliver immediate feedback, adaptive explanations, and tailored learning pathways to meet diverse student needs, while also assisting with problem-solving tasks and automating routine academic processes (S. Guo et al., 2024; Smolansky et al., 2023).”
Dron, J. (2023) · Digital · doi:10.3390/digital3040020 · Cited by 22 · see citing works
One year in the classroom with ChatGPT: empirical insights and transformative impacts
Guo, F., Li, T., & Cunningham, C. J. L. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1574477 · Cited by 32 · see citing works
Reimer, E. C. (2024) · Social Sciences · doi:10.3390/socsci13120648 · Cited by 18 · see citing works
Adapting to AI: Reimagining the Role of Assessment Professionals
Miller, W. T. (2024) · Intersection A Journal at the Intersection of Assessment and Learning · doi:10.61669/001c.121439 · Cited by 18 · see citing works
Editorial: Artificial Intelligence is Awesome, but Good Teaching Should Always Come First.
Crawford, J., Vallis, C., Yang, J., Fitzgerald, R., O'Dea, C., & Cowling, M. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/1.20.7.01 · Cited by 18 · see citing works
Asamoah, M. K., & Amarteifio, J. (2025) · Discover Education · doi:10.1007/s44217-025-00593-5 · Cited by 24 · see citing works
Reconsidering teacher assessment literacy in GenAI-enhanced environments: A scoping review
Cui, Y. H., Meng, Y., & Tang, L. (2025) · Teaching and Teacher Education · doi:10.1016/j.tate.2025.105163 · Cited by 23 · see citing works
Crafting Tomorrow’s Evaluations: Assessment Design Strategies in the Era of Generative AI
Kadel, R., Mishra, B. K., Shailendra, S., Abid, S., Rani, M., & Mahato, S. P. (2024) · International Symposium on Educational Technology · doi:10.1109/iset61814.2024.00012 · Cited by 18 · see citing works
“The authors in [9] have discussed innovative assessment strategies for addressing GenAI challenges in education, such as prioritising process over product, using oral assessments, employing AI detection tools, and promoting critical thinking.”
BackgroundEngineering Educators' Perspectives on the Impact of Generative AI in Higher Education
Dewan, U., Hingle, A., McDonald, N., & Johri, A. (2025) · 2025 IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon62633.2025.11016518 · Cited by 16 · see citing works
“An important theme across these studies is the experimental nature of educator’s engagements with GenAI, frequently testing its capabilities by observing how it handles their assignments and assessments [3], [4], [14], [28].”
Hershkovitz, A., Tabach, M., Reich, Y., Lurie, L., & Cholcman, T. (2025) · Systems · doi:10.3390/systems13070518 · Cited by 23 · see citing works
Orhan, A., Yıldız, T. A., & Yağcı, Ş. Ç. (2024) · Journal of Research on Technology in Education · doi:10.1080/15391523.2024.2437744 · Cited by 18 · see citing works
“Therefore, based on this theoretical framework, it can be said that the success of integrating these technologies into educational practices heavily depends on the willingness and readiness of both teachers and students to engage with GenAI (Smolansky et al., 2023).”
Generative artificial intelligence in fifth-generation education systems: A systematic review
Chakraborty, S. (2026) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2026.114463 · Cited by 50 · see citing works
“This change from a model that is solely assessment-focused to one that emphasises interactive learning and continuous improvement contributes to the development of a more vibrant and encouraging learning environment [25].”
Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AIPreprint
Kadel, R., Mishra, B. K., Shailendra, S., Abid, S., Rani, M., & Mahato, S. P. (2024) · doi:10.36227/techrxiv.171502818.84241801/v1 · Cited by 25 · see citing works
Mathew, R., & Stefaniak, J. E. (2024) · TechTrends · doi:10.1007/s11528-024-00964-z · Cited by 15 · see citing works
“AI-powered systems can provide prompt and consistent evaluations, reducing the burden on faculty members while also offering students faster feedback (Baidoo-Anu & Ansah, 2023; Smolansky et al., 2023).”
Examining Student and Teacher Perspectives on Undisclosed Use of Generative AI in Academic Work
Adnin, R., Pandkar, A., Yao, B., Wang, D., & Das, M. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713393 · Cited by 16 · see citing works
“These tools can negatively affect students’ learning gains when they submit AI-generated responses as their assignments without understanding the underlying concepts [51, 61, 87, 89] and provide an unfair advantage over peers [108].”
A tutorial for integrating generative AI in mixed methods data analysis
Combrinck, C. (2024) · Discover Education · doi:10.1007/s44217-024-00214-7 · Cited by 32 · see citing works
“Students are worried about the impact generative AI will have on their development, and the academy is concerned about academic integrity and the impact on assessment [46].”
Bernik, A., Radošević, D., & Čep, A. (2025) · Applied Sciences · doi:10.3390/app151810055 · Cited by 19 · see citing works
Assessing law students in a GenAI world to create knowledgeable future lawyers
Head, A., & Willis, S. (2024) · International Journal of the Legal Profession · doi:10.1080/09695958.2024.2379785 · Cited by 13 · see citing works
“Student views on using GenAI in higher education have received some attention (Chan 2023; Chan and Hu 2023; Farhi et al. 2023; Firat 2023; Huallpa et al. 2023; Shoufan 2023; Smolansky et al. 2023).”
Editorial: Harnessing the Power of Large Language Models in Agricultural Safety & Health
Shutske, J. M. (2023) · Journal of Agricultural Safety and Health · doi:10.13031/jash.15841 · Cited by 13 · see citing works
Cheung, L. H., & Dall’Asta, J. C. (2024) · Eídos · doi:10.29019/eidos.v17i23.1282 · Cited by 12 · see citing works
Labib, W. A., Abdelsattar, A., Abowardah, E. S., Abdelalim, M. F., & Mahmoud, H. (2025) · Sustainability · doi:10.3390/su172210029 · Cited by 16 · see citing works
Enhancing Critical Thinking with Gen AI: A Literature Review
Hikmawati, A., & Mohammad, N. K. (2025) · Buletin Edukasi Indonesia · doi:10.56741/bei.v4i01.764 · Cited by 15 · see citing works
“This aligns with the necessity of establishing robust AI literacy programs and regulatory frameworks to guide students and educators in using these tools responsibly, ensuring their integration aligns with academic integrity and societal values [3],[10].”
Generative AI Under Scrutiny: Assessing the Risks and Challenges in Diverse Domains
Nidhisree, C., Paul, A., Venunadh, A., & Bhowmick, R. S. (2024) · IEEE International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA) · doi:10.1109/icccmla63077.2024.10871350 · Cited by 10 · see citing works
“[11] Education 2.”
InfluentialKharrufa, A., Alghamdi, S. S., Aziz, A., & Bull, C. (2025) · ACM Transactions on Computing Education · doi:10.1145/3779296 · Cited by 16 · see citing works
“As with other research, their findings also reveal concerns about academic integrity and challenges to learning for novice students, but they also emphasize the rich pedagogical opportunities that these tools offer.”
Pudasaini, S., Miralles-Pechuán, L., Lillis, D., & Salvador, M. L. (2024) · arXiv · doi:10.48550/arxiv.2407.13105 · Cited by 8 · see citing works
“C Y ] 4 J un 2024 students on such tools leads to the loss of creativity and learning ability [7].”
BackgroundTHE ROLE OF GENERATIVE AI-POWERED PERSONAS IN DEVELOPING GRADUATE INTERVIEWING SKILLS
Sabbaghan, S., & Brown, B. (2024) · International journal on innovations in online education · doi:10.1615/intjinnovonlineedu.2024051770 · Cited by 9 · see citing works
Generative AI and Teachers - For Us or Against Us? A Case Study
Pettersson, J., Hult, E., Eriksson, T., & Adewumi, O. (2024) · Linköping electronic conference proceedings · doi:10.3384/ecp208005 · Cited by 10 · see citing works
Exploring University Staff’s Perceptions of Using Generative Artificial Intelligence at University
Whitbread, M., Hayes, C., Prabhakar, S., & Upsher, R. J. (2025) · Education Sciences · doi:10.3390/educsci15030367 · Cited by 9 · see citing works
Chen, S., Metoyer, R., Le, K. H., Acunin, A., Molnar, I., Ambrose, A., Lang, J., Chawla, N. V., & Metoyer, R. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98462-4_22 · Cited by 10 · see citing works
Basil, M., Ahmed, W., Hajeomar, R., Strawbridge, J., Lynch, M. R., & Mukhalalati, B. (2026) · BMC Medical Education · doi:10.1186/s12909-025-08527-3 · Cited by 13 · see citing works
“To address this need, suggested strategies include incorporating AI detection tools, prioritizing the learning process over outcomes, and expanding the use of oral examinations [185].”
Artificial Intellegence (AI) dan Dampaknya Dalam Distorsi Pendidikan Islam
Hakim, F., Fadlillah, A. N., & Rofiq, M. N. (2024) · Urwatul Wutsqo Jurnal Studi Kependidikan dan Keislaman · doi:10.54437/urwatulwutsqo.v13i1.1330 · Cited by 9 · see citing works
Papyshev, G. (2024) · Journal of Asian Public Policy · doi:10.1080/17516234.2024.2370716 · Cited by 10 · see citing works
“It is intriguing to note that, while students perceive the contribution of AI as largely positive for specific tasks, such as programming (Yilmaz & Karaoglan Yilmaz, 2023), they also express concerns about potential drawbacks, including a potential decrease in creativity (Smolansky et al., 2023).”
Ethical Uses of Generative AI in Assessment: Student Perceptions in UK Contexts
O’Dea, X., Bale, R., Chiu, Y.-L. T., Suleymenova, K., Tinker, A. J., & Stoker, R. (2025) · Evaluation Review · doi:10.1177/0193841x251399712 · Cited by 8 · see citing works
Memarian, B., & Doleck, T. (2025) · SN Computer Science · doi:10.1007/s42979-025-04569-y · Cited by 14 · see citing works
“Similarly, Smolansky et al. [ 107 ] measured and compared students’ and faculty’s perceptions.”
InfluentialChinese EFL learners’ engagement with ChatGPT feedback on academic writing: A case study in Malaysia
Kailin, Z., & Saeed, M. A. (2025) · Computers & composition/Computers and composition · doi:10.1016/j.compcom.2025.102976 · Cited by 18 · see citing works
Razi, A., Bouzoubaa, L. A., Pessianzadeh, A., Seberger, J. S., & Rezapour, R. (2025) · Research Square · doi:10.21203/rs.3.rs-5686084/v1 · Cited by 13 · see citing works
Kumar, S. S., Lones, M. A., Maarek, M., & Zantout, H. (2024) · International Workshop on Large Language Models for Code (LLM4Code) · doi:10.1145/3643795.3648380 · Cited by 7 · see citing works
Artificial Intelligence Policies in Higher Education: A Randomized Field Experiment
Greenspan, R. L. (2025) · Journal of Criminal Justice Education · doi:10.1080/10511253.2025.2449603 · Cited by 7 · see citing works
Developing students’ agency and voice by using generative AI in an online EAP module
Smirnova, L. Y. (2025) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2025.2538781 · Cited by 7 · see citing works
Assessment Validity in the Age of Generative AI: A Natural Experiment
Brattli, H., Utne, A. S., & Lynch, M. (2026) · Informatics · doi:10.3390/informatics13040056 · Cited by 8 · see citing works
BoilerTAI: A Platform for Enhancing Instruction Using Generative AI in Educational Forums
Sinha, A., Goyal, S., Sy, Z., Kuperus, R., Dickey, E., & Bejarano, A. (2024) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10893137 · Cited by 7 · see citing works
“…context and evidence in AI-generated responses, concerns about academic integrity, potential for hallucinations (incorrect or misleading results) [35]–[37], and concerns like the Junior-Year Wall [38] are addressed by having TAs add context and corroborate facts, effectively saving time and…”
Digital Assessment in Higher Education: Sustainable Trends and Emerging Frontiers in the AI Era
Lelescu, A., & Kabiraj, S. (2024) · Lecture notes in educational technology · doi:10.1007/978-981-97-6136-4_2 · Cited by 6 · see citing works
Domain-Tailored Generative AI for Personalized Assistant
Jiang, N., Hasanzadeh, S., & Duffy, V. G. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-76809-5_17 · Cited by 6 · see citing works
Alhassan, M. D., Adam, I. O., Iddrisu, A., et al. (2025) · Digital Policy Regulation and Governance · doi:10.1108/dprg-01-2024-0003 · Cited by 6 · see citing works
Poornesh, M. (2025) · The Clearing House A Journal of Educational Strategies Issues and Ideas · doi:10.1080/00098655.2025.2493717 · Cited by 6 · see citing works
“Assessing the validity and reliability of Generative AI outputs is essential for upholding academic standards (Smolansky et al. 2023).”
Revolutionizing Creative Education
Akbar, K., Nyika, F. D., & Mbonye, V. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-2418-9.ch012 · Cited by 6 · see citing works
From Assistance to Misconduct: Unpacking the Complex Role of Generative AI in Student Learning
Axelsson, A., Wallgren, D. T., Verma, U., Cajander, Å., Daniels, M., Eckerdal, A., & McDermott, R. (2024) · 2024 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10893133 · Cited by 5 · see citing works
“In a survey involving students and educators, the majority were concerned about academic integrity and favored adapted assessments that assume GenAI usage while encouraging critical thinking [4].”
Unlocking Insights: Investigating Student AI Tutor Interactions in a Large Introductory STEM Course
Russell, J. M., Smith, A. M., George, S., Pratt, J., Fodale, B., Monk, C., & Brummett, A. E. (2025) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3706468.3706524 · Cited by 7 · see citing works
Kusam, V. A., Shrestha, S., Kattan, K. A., Maxim, B. R., & Song, Z. (2024) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10893118 · Cited by 5 · see citing works
“This is particularly crucial in online classes where students may not receive much one-on-one attention [20], [28], [29].”
AI Across Borders: Exploring Perceptions and Interactions in Higher Education
Gerard, J., Singh, S. P., Macleod, M., McKay, M., Rivoire, A., Chakraborty, T., & Singh, M. (2025) · Education Sciences · doi:10.3390/educsci15081039 · Cited by 8 · see citing works
“We also observed the usefulness of optional text comments in better assessing the perception, for example, by enlisting the use cases as well as potential risks to better map their awareness and perception around GenAI.”
The early wave of ChatGPT research: A review and future agenda
Busch, P., Hausvik, G. I., & Nielsen, J. (2025) · Comput. Hum. Behav. Artif. Humans · doi:10.1016/j.chbah.2025.100213 · Cited by 9 · see citing works
Applying the AI assessment scale in writing and translation for EFL
Roe, J., Perkins, M., & Furze, L. (2025) · Artificial Intelligence in Education · doi:10.1108/aiie-02-2025-0034 · Cited by 20 · see citing works
“This is important given the gap between learners and teachers’ opinions on how to use AI (Smolansky et al., 2023).”
Employing generative AI applications in learning
Nadif, B., Zemrani, M. Z., Hammou, B. A., Mansour, S.-E., Fakhrou, A., & Bouih, A. (2025) · American Journal of STEM Education · doi:10.32674/vt55r634 · Cited by 6 · see citing works
Xu, X., & Thien, L. M. (2026) · European Journal of Education · doi:10.1111/ejed.70520 · Cited by 10 · see citing works
Japanese University EFL Student Insights on the Emerging ChatGPT Phenomenon
Price, G. (2024) · International Journal of Education Learning and Development · doi:10.37745/ijeld.2013/vol12n583100 · Cited by 5 · see citing works
“…2023; Chan, 2023; Chan & Hu, 2023; Cotton et al., 2023; Fitria, 2023; Fyfe, 2023; Kanabar, 2023; Mohammadkarimi, 2023; Price & Sakellarios, 2023; Smolansky et al., 2023; Van Wyk, 2024) have been published concerning ethics and assessing the use of AI-generated writing in student assignments.”
BackgroundComparative Performance of GPT-4, RAG-Augmented GPT-4, and Students in MOOCs
Miladi, F., Psyché, V., & Daniel Lemire, A. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-65996-6_7 · Cited by 5 · see citing works
“Instructors should adopt a more sustainable assessment approach that priori-tizes the cultivation of higher-order cognitive abilities, including critical thinking [18], problem-solving, and creativity [19].”
BackgroundGuruge, D. B., Kadel, R., Shailendra, S., & Sharma, A. (2025) · Societies · doi:10.3390/soc15010011 · Cited by 5 · see citing works
- Authors
- Smolansky, A., Cram, A., Raduescu, C., Zeivots, S., Huber, E., & Kizilcec, R. F.
- Affiliations
- Cornell University (US)
- The University of Sydney (AU)
- Cornell University, Ithaca, NY, USA
- Venue
- Proceedings of the Tenth ACM Conference on Learning @ Scale
- Publisher
- ACM
- Published
- 2023-07-20
- Pages
- 378-382
- OpenAlex
- W4384662087
- Cited by
- 275
- References
- 6
- Citations by year
- 2026: 76 · 2025: 116 · 2024: 79 · 2023: 4
- FWCI
- 63.59
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Conference on Learning @ Scale (L@S) (publishedVersion)
- Funders
- USyd-Cornell Partnership Collaboration Awards (PCA) (1178246719)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- generative AI, ChatGPT, higher education assessment, academic integrity, student perceptions, educator perspectives, assessment reform, critical thinking, creativity, higher-order thinking skills, artificial intelligence in education
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-23.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-23.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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